Self-reported Mobility in Older Patients Predicts Early Postoperative Outcomes after Elective Noncardiac Surgery

10 years of prehabilitation: From theory to clinical practice

In recent years, prehabilitation has generated high expectations as an innovative preoperative strategy to enhance clinical outcomes following surgery. Several studies have demonstrated that multimodal programs are effective in improving patients' health status and cardiopulmonary reserve, allowing them to undergo surgery in better conditions and, consequently, reducing the incidence of postoperative complications. Most publications describe proof-of-concept studies, and literature about their implementation is more limited. The implementation of these programs requires new resources and significant organizational effort. In this paper, we share our experience implementing a multimodal prehabilitation program as a mainstream service at a tertiary hospital. Although there are still many unknowns regarding the optimal selection of patients, as well as the duration and components of the program, this article describes our journey in this field, aiming to provide insight for teams interested in developing a similar project.

Interdisciplinary Protocol for Surgery in Older Persons: Development and Implementation

As the population ages, more older adults will undergo surgical procedures, and common physiologic changes can raise the risk for surgical complications while increasing morbidity and mortality. In conjunction with the National Surgical Quality Improvement Program, we piloted a comprehensive and interdisciplinary assessment and intervention protocol for perioperative care for patients aged ≥75 years undergoing elective general, gynecology-oncologic, and orthopedic surgery. The intervention included screening tools for cognitive, functional, and nutritional deficits, a Geriatric Nurse Champion on each inpatient surgical unit, and an interdisciplinary Geriatric Surgery Quality Committee. Our intervention group was compared to surgical patients during the same time period 1 year prior to the intervention, and the groups were well matched in demographics and comorbidities. The intervention group had significantly higher rates of advance care plan documentation in analysis of all patients (P < .001) and in subgroup analysis of those 85 and older (P = .006). The preintervention group had less postoperative delirium compared to the postintervention group but it was not significant and there was no difference in length of stay between groups. Various explanations for the minimal impact of the protocol exist: small sample size, presence of other hospital initiatives to reduce pressure ulcer and delirium, and clinician's awareness of project planning that led to incorporating ideas prior to official implementation. Future research implementing this protocol in naïve and/or underperforming institutions may demonstrate a greater effect. Larger sample size as well as implementation in other surgical fields may reveal a significant impact. However, if additional study does not reveal a meaningful impact of a comprehensive geriatric assessment for surgical patients, then consideration must be made regarding unrecognized factors in surgical care for older adults or perhaps that factors cannot be mitigated in older adults because they are intrinsically a higher surgical risk.

The comparative and added prognostic value of biomarkers to the Revised Cardiac Risk Index for preoperative prediction of major adverse cardiac events and all-cause mortality in patients who undergo noncardiac surgery

BACKGROUND

The Revised Cardiac Risk Index (RCRI) is a widely acknowledged prognostic model to estimate preoperatively the probability of developing in-hospital major adverse cardiac events (MACE) in patients undergoing noncardiac surgery. However, the RCRI does not always make accurate predictions, so various studies have investigated whether biomarkers added to or compared with the RCRI could improve this.

OBJECTIVES

Primary: To investigate the added predictive value of biomarkers to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Secondary: To investigate the prognostic value of biomarkers compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Tertiary: To investigate the prognostic value of other prediction models compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery.

SEARCH METHODS

We searched MEDLINE and Embase from 1 January 1999 (the year that the RCRI was published) until 25 June 2020. We also searched ISI Web of Science and SCOPUS for articles referring to the original RCRI development study in that period.

SELECTION CRITERIA

We included studies among adults who underwent noncardiac surgery, reporting on (external) validation of the RCRI and: - the addition of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of the RCRI to other models. Besides MACE, all other adverse outcomes were considered for inclusion.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form based on the CHARMS checklist. Independent pairs of authors screened references, extracted data and assessed risk of bias and concerns regarding applicability according to PROBAST. For biomarkers and prediction models that were added or compared to the RCRI in ≥ 3 different articles, we described study characteristics and findings in further detail. We did not apply GRADE as no guidance is available for prognostic model reviews.

MAIN RESULTS

We screened 3960 records and included 107 articles.   Over all objectives we rated risk of bias as high in ≥ 1 domain in 90% of included studies, particularly in the analysis domain. Statistical pooling or meta-analysis of reported results was impossible due to heterogeneity in various aspects: outcomes used, scale by which the biomarker was added/compared to the RCRI, prediction horizons and studied populations.  Added predictive value of biomarkers to the RCRI Fifty-one studies reported on the added value of biomarkers to the RCRI. Sixty-nine different predictors were identified derived from blood (29%), imaging (33%) or other sources (38%). Addition of NT-proBNP, troponin or their combination improved the RCRI for predicting MACE (median delta c-statistics: 0.08, 0.14 and 0.12 for NT-proBNP, troponin and their combination, respectively). The median total net reclassification index (NRI) was 0.16 and 0.74 after addition of troponin and NT-proBNP to the RCRI, respectively. Calibration was not reported. To predict myocardial infarction, the median delta c-statistic when NT-proBNP was added to the RCRI was 0.09, and 0.06 for prediction of all-cause mortality and MACE combined. For BNP and copeptin, data were not sufficient to provide results on their added predictive performance, for any of the outcomes. Comparison of the predictive value of biomarkers to the RCRI  Fifty-one studies assessed the predictive performance of biomarkers alone compared to the RCRI. We identified 60 unique predictors derived from blood (38%), imaging (30%) or other sources, such as the American Society of Anesthesiologists (ASA) classification (32%). Predictions were similar between the ASA classification and the RCRI for all studied outcomes. In studies different from those identified in objective 1, the median delta c-statistic was 0.15 and 0.12 in favour of  BNP and NT-proBNP alone, respectively, when compared to the RCRI, for the prediction of MACE. For C-reactive protein, the predictive performance was similar to the RCRI. For other biomarkers and outcomes, data were insufficient to provide summary results. One study reported on calibration and none on reclassification. Comparison of the predictive value of other prognostic models to the RCRI   Fifty-two articles compared the predictive ability of the RCRI to other prognostic models. Of these, 42% developed a new prediction model, 22% updated the RCRI, or another prediction model, and 37% validated an existing prediction model. None of the other prediction models showed better performance in predicting MACE than the RCRI. To predict myocardial infarction and cardiac arrest, ACS-NSQIP-MICA had a higher median delta c-statistic of 0.11 compared to the RCRI. To predict all-cause mortality, the median delta c-statistic was 0.15 higher in favour of ACS-NSQIP-SRS compared to the RCRI. Predictive performance was not better for CHADS₂, CHA₂DS₂-VASc, R₂CHADS₂, Goldman index, Detsky index or VSG-CRI compared to the RCRI for any of the outcomes. Calibration and reclassification were reported in only one and three studies, respectively.

AUTHORS' CONCLUSIONS

Studies included in this review suggest that the predictive performance of the RCRI in predicting MACE is improved when NT-proBNP, troponin or their combination are added. Other studies indicate that BNP and NT-proBNP, when used in isolation, may even have a higher discriminative performance than the RCRI. There was insufficient evidence of a difference between the predictive accuracy of the RCRI and other prediction models in predicting MACE. However, ACS-NSQIP-MICA and ACS-NSQIP-SRS outperformed the RCRI in predicting myocardial infarction and cardiac arrest combined, and all-cause mortality, respectively. Nevertheless, the results cannot be interpreted as conclusive due to high risks of bias in a majority of papers, and pooling was impossible due to heterogeneity in outcomes, prediction horizons, biomarkers and studied populations. Future research on the added prognostic value of biomarkers to existing prediction models should focus on biomarkers with good predictive accuracy in other settings (e.g. diagnosis of myocardial infarction) and identification of biomarkers from omics data. They should be compared to novel biomarkers with so far insufficient evidence compared to established ones, including NT-proBNP or troponins. Adherence to recent guidance for prediction model studies (e.g. TRIPOD; PROBAST) and use of standardised outcome definitions in primary studies is highly recommended to facilitate systematic review and meta-analyses in the future.

How can we minimize the risks by optimizing patient's condition shortly before thoracic surgery?

The “moderate-to-high-risk” surgical patient is typically older, frail, malnourished, suffering from multiple comorbidities and presenting with unhealthy life style such as smoking, hazardous drinking and sedentarity. Poor aerobic fitness, sarcopenia and “toxic” behaviors are modifiable risk factors for major postoperative complications. The physiological challenge of lung cancer surgery has been likened to running a marathon. Therefore, preoperative patient optimization or “ prehabilitation “ should become a key component of improved recovery pathways to enhance general health and physiological reserve prior to surgery. During the short preoperative period, the patients are more receptive and motivated to adhere to behavioral interventions (e.g., smoking cessation, weaning from alcohol, balanced food intake and active mobilization) and to follow a structured exercise training program. Sufficient protein intake should be ensured (1.5–2 g/kg/day) and nutritional defects should be corrected to restore muscle mass and strength. Currently, there is strong evidence supporting the effectiveness of various modalities of physical training (endurance training and/or respiratory muscle training) to enhance aerobic fitness and to mitigate the risk of pulmonary complications while reducing the hospital length of stay. Multimodal interventions should be individualized to the patient's condition. These bundle of care are more effective than single or sequential intervention owing to synergistic benefits of education, nutritional support and physical training. An effective prehabilitation program is necessarily patient-centred and coordinated among health care professionals (nurses, primary care physician, physiotherapists, nutritionists) to help the patient regain some control over the disease process and improve the physiological reserve to sustain surgical stress.

A pilot study of aquatic prehabilitation in adults with knee osteoarthritis undergoing total knee arthroplasty - short term outcome

BACKGROUND

Knee osteoarthritis (KOA) is increasingly more prevalent and significant number of patients require knee arthroplasty. Although knee arthroplasty is generally successful, it takes months to recover physical function. Preoperative physical function is known to predict postoperative outcomes and exercise can improve preoperative physical function. However, patients with KOA have difficulty exercise on land due to pain and stiffness, while water exercise can be better tolerated. We hypothesized that preoperative water exercise to improve preoperative physical function will improve postoperative outcomes after total knee arthroplasty (TKA).

METHODS

We enrolled 43 participants who were scheduled for elective TKA in 4-8 weeks and scored at or below 50th percentile in mobility assessment tool-sf (MAT-sf). All enrolled participants were assessed on 1) clinical osteoarthritis symptom severity using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), 2) physical function using Short Physical Performance Battery (SPPB), 3) self-reported mobility using Mobility Assessment Tool-short form (MAT-sf), 4) depression using Geriatric Depression Scale-short form (GDS-sf), 5) cognitive function using Montreal Cognitive Assessment (MoCA). Blood samples for high-sensitivity-C-reactive protein (hs-CRP), tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) were stored at - 80 °C then all samples were analyzed together. All the enrolled participants were randomly assigned to the aquatic exercise intervention (AEI) or usual care group. Sixty minute sessions of AEI was conducted three times a week for 4-8 weeks. Participants in both groups were evaluated within 1 week before their scheduled surgery, as well as 4 weeks after the surgery.

RESULTS

The mean age was 67.1 (±6.2), 44% were female, 74% were White. There is no statistically significant difference in combined outcome of any complication, unscheduled ER visit, and disposition to nursing home or rehab facility by AEI. However, AEI was associated with more favorable outcomes: WOMAC scores (p < 0.01), chair-stand (p = 0.019), MAT-sf as well as improved depression (p = 0.043) and cognition (p = 0.008).

CONCLUSION

4-8 weeks of aquatic exercise intervention resulted in improved functional outcomes as well as improved depression and cognition in elderly patients undergoing TKA. A larger study is warranted to explore the role of water exercise in clinical and functional outcomes of TKA.

Influence of Frailty on Outcome in Older Patients Undergoing Non-Cardiac Surgery - A Systematic Review and Meta-Analysis

Frailty is increasingly recognized as a better predictor of adverse postoperative events than chronological age. The objective of this review was to systematically evaluate the effect of frailty on postoperative morbidity and mortality. Studies were included if patients underwent non-cardiac surgery and if frailty was measured by a validated instrument using physical, cognitive and functional domains. A systematic search was performed using EMBASE, MEDLINE, Web of Science, CENTRAL and PubMed from 1990 - 2017. Methodological quality was assessed using an assessment tool for prognosis studies. Outcomes were 30-day mortality and complications, one-year mortality, postoperative delirium and discharge location. Meta-analyses using random effect models were performed and presented as pooled risk ratios with confidence intervals and prediction intervals. We included 56 studies involving 1.106.653 patients. Eleven frailty assessment tools were used. Frailty increases risk of 30-day mortality (31 studies, 673.387 patients, risk ratio 3.71 [95% CI 2.89-4.77] (PI 1.38-9.97; I2=95%) and 30-day complications (37 studies, 627.991 patients, RR 2.39 [95% CI 2.02-2.83). Risk of 1-year mortality was threefold higher (six studies, 341.769 patients, RR 3.40 [95% CI 2.42-4.77]). Four studies (N=438) reported on postoperative delirium. Meta-analysis showed a significant increased risk (RR 2.13 [95% CI 1.23-3.67). Finally, frail patients had a higher risk of institutionalization (10 studies, RR 2.30 [95% CI 1.81- 2.92]). Frailty is strongly associated with risk of postoperative complications, delirium, institutionalization and mortality. Preoperative assessment of frailty can be used as a tool for patients and doctors to decide who benefits from surgery and who doesn't.

A simplified (modified) Duke Activity Status Index (M-DASI) to characterise functional capacity: a secondary analysis of the Measurement of Exercise Tolerance before Surgery (METS) study

BACKGROUND

Accurate assessment of functional capacity, a predictor of postoperative morbidity and mortality, is essential to improving surgical planning and outcomes. We assessed if all 12 items of the Duke Activity Status Index (DASI) were equally important in reflecting exercise capacity.

METHODS

In this secondary cross-sectional analysis of the international, multicentre Measurement of Exercise Tolerance before Surgery (METS) study, we assessed cardiopulmonary exercise testing and DASI data from 1455 participants. Multivariable regression analyses were used to revise the DASI model in predicting an anaerobic threshold (AT) >11 ml kg^-1 min^-1 and peak oxygen consumption (VO₂ peak) >16 ml kg^-1 min^-1, cut-points that represent a reduced risk of postoperative complications.

RESULTS

Five questions were identified to have dominance in predicting AT>11 ml kg^-1 min^-1 and VO₂ peak>16 ml.kg^-1min^-1. These items were included in the M-DASI-5Q and retained utility in predicting AT>11 ml.kg^-1.min^-1 (area under the receiver-operating-characteristic [AUROC]-AT: M-DASI-5Q=0.67 vs original 12-question DASI=0.66) and VO₂ peak (AUROC-VO2 peak: M-DASI-5Q 0.73 vs original 12-question DASI 0.71). Conversely, in a sensitivity analysis we removed one potentially sensitive question related to the ability to have sexual relations, and the ability of the remaining four questions (M-DASI-4Q) to predict an adequate functional threshold remained no worse than the original 12-question DASI model. Adding a dynamic component to the M-DASI-4Q by assessing the chronotropic response to exercise improved its ability to discriminate between those with VO₂ peak>16 ml.kg^-1.min^-1 and VO₂ peak<16 ml.kg^-1.min^-1.

CONCLUSIONS

The M-DASI provides a simple screening tool for further preoperative evaluation, including with cardiopulmonary exercise testing, to guide perioperative management.

Accuracy and Feasibility of Clinically Applied Frailty Instruments before Surgery

Background

A barrier to routine preoperative frailty assessment is the large number of frailty instruments described. Previous systematic reviews estimate the association of frailty with outcomes, but none have evaluated outcomes at the individual instrument level or specific to clinical assessment of frailty, which must combine accuracy with feasibility to support clinical practice.

Methods

The authors conducted a preregistered systematic review (CRD42019107551) of studies prospectively applying a frailty instrument in a clinical setting before surgery. Medline, Excerpta Medica Database, Cochrane Library and the Comprehensive Index to Nursing and Allied Health Literature, and Cochrane databases were searched using a peer-reviewed strategy. All stages of the review were completed in duplicate. The primary outcome was mortality and secondary outcomes reflected routinely collected and patient-centered measures; feasibility measures were also collected. Effect estimates were pooled using random-effects models or narratively synthesized. Risk of bias was assessed.

Results

Seventy studies were included; 45 contributed to meta-analyses. Frailty was defined using 35 different instruments; five were meta-analyzed, with the Fried Phenotype having the largest number of studies. Most strongly associated with: mortality and nonfavorable discharge was the Clinical Frailty Scale (odds ratio, 4.89; 95% CI, 1.83 to 13.05 and odds ratio, 6.31; 95% CI, 4.00 to 9.94, respectively); complications was associated with the Edmonton Frail Scale (odds ratio, 2.93; 95% CI, 1.52 to 5.65); and delirium was associated with the Frailty Phenotype (odds ratio, 3.79; 95% CI, 1.75 to 8.22). The Clinical Frailty Scale had the highest reported measures of feasibility.

Conclusions

Clinicians should consider accuracy and feasibility when choosing a frailty instrument. Strong evidence in both domains support the Clinical Frailty Scale, while the Fried Phenotype may require a trade-off of accuracy with lower feasibility.

Editor’s Perspective

What We Already Know about This Topic

What This Article Tells Us That Is New

Pathways, Contributors, and Correlates of Functional Limitation Across Specialties: Workshop Summary

Traditional clinical care models focus on the measurement and normalization of individual organ systems and de-emphasize aspects of health related to the integration of physiologic systems. Measures of physical, cognitive and sensory, and psychosocial or emotional function predict important health outcomes like death and disability independently from the severity of a specific disease, cumulative co-morbidity, or disease severity measures. A growing number of clinical scientists in several subspecialties are exploring the utility of functional assessment to predict complication risk, indicate stress resistance, inform disease screening approaches and risk factor interpretation, and evaluate care. Because a substantial number of older adults in the community have some form of functional limitation, integrating functional assessment into clinical medicine could have a large impact. Although interest in functional implications for health and disease management is growing, the science underlying functional capacity, functional limitation, physical frailty, and functional metrics is often siloed among different clinicians and researchers, with fragmented concepts and methods. On August 25-26, 2016, participants at a trans-disciplinary workshop, supported by the National Institute on Aging and the John A. Hartford Foundation, explored what is known about the pathways, contributors, and correlates of physical, cognitive, and sensory functional measures across conditions and disease states; considered social determinants and health disparities; identified knowledge gaps, and suggested priorities for future research. This article summarizes those discussions.

Self-Reported Physical Function As a Predictor of Hospitalization in the Lifestyle Interventions and Independence for Elders Study

OBJECTIVES

To explore whether baseline scores on the Mobility Assessment Tool-short form (MAT-sf), a brief, animated, computer-based means of assessing mobility that predicts mobility disability, are associated with number of hospitalizations and time to first hospitalization over a median follow-up of 2.7 years.

DESIGN

Post hoc analysis of prospectively gathered data from the Lifestyle Interventions and Independence for Elders (LIFE) Study, a randomized clinical trial of lifestyle interventions to preserve mobility in older adults.

SETTING

Eight U.S. academic medical centers.

PARTICIPANTS

Of 1,635 sedentary community-dwelling older adults enrolled in LIFE, 1,574 completed baseline physical function screening including the MAT-sf, with baseline scores ranging from 30.2 (low function) to 69.8 (high function) on a scale from 30 to 80.

MEASUREMENTS

Number of hospitalizations and time to first hospitalization, adjusted for age, sex, race, living alone, clinical site, baseline comorbidities, number of prescription medications, and cognition.

RESULTS

Of the 1,557 participants with data regarding hospitalization status, 726 (47%) had at least 1 hospitalization; 78% of these had 1 or 2 hospitalizations. For every 10-point lower MAT-sf score, the rate of all hospitalizations was 19% higher in those with lower scores (adjusted rate ratio=1.20, 95% confidence interval (CI)=1.08-1.32, p<.001). Lower baseline MAT-sf scores were also associated with greater risk of first hospitalization (adjusted hazard ratio=1.20, 95% CI=1.09-1.32, p<.01, per 10-point lower MAT-sf score).

CONCLUSION

Low MAT-sf scores identify older adults at risk of hospitalization; further study is needed to test interventions to reduce hospitalizations in these individuals.

Self-reported mobility as a preoperative risk assessment tool in older surgical patients compared to the American College of Surgeons National Surgical Quality Improvement Program

Background

The American College of Surgeons National Surgical Quality Improvement Program (NSQIP®) developed a surgical risk calculator using data from 1.4 million patients and including 1557 unique Current Procedural Terminology (CPT) codes. Although this calculator demonstrated excellent performance in predicting postoperative mortality, morbidity, and six surgical complications, it was not developed specifically for use in older surgical patients who have worse surgical outcomes and additional unique risk factors compared to younger adults. We aimed to test the ability of a simple self-reported mobility tool to predict postoperative outcomes in the older surgical population compared to the NSQIP.

Methods

We used data from a prospective cohort study that enrolled 197 older surgical patients (≥ 69 years) undergoing various elective surgeries and assessed 30-day surgical outcomes. Statistical models included data from the Mobility Assessment Tool-short form (MAT-sf) alone, covariates alone, and MAT-sf data and covariates. We used leave-one-out (LOO) cross-validation of the models within our cohort and compared their performance for predicting postoperative outcomes against the NSQIP calculator based on receiver operating characteristic area under the curve (ROC AUC).

Results

Patients with poor self-reported mobility experienced higher rates of postoperative complications and nursing home placement. There was no difference in performance between any of our models and the NSQIP calculator (p > 0.1), with AUC between 0.604 and 0.697 for predicting postoperative complications and 0.653 and 0.760 for predicting nursing home placement. All models also predicted a length of stay (LOS) similar to the actual LOS.

Conclusion

Mobility assessment alone using MAT-sf can predict postoperative complications, nursing home placement, and LOS for older surgical patients, with accuracy comparable to that of the NSQIP calculator. The simplicity of this noninvasive risk assessment tool makes it an attractive alternative to the NSQIP calculator that requires 20 patient predictors and the planned procedure, or CPT code to predict the chance that patients will have 15 different adverse outcomes following surgery.

Self- vs proxy-reported mobility using the mobility assessment tool-short form in elderly preoperative patients

Background

Mobility is fundamental to maintenance of an independent lifestyle and can predict clinical outcomes after health events among older individuals. However, certain clinical situations do not accommodate physical or self-assessments. This investigation examines whether proxy-reported assessments of function using the Mobility Assessment Tool-short (MAT-sf) form is a reliable alternative.

Methods

Sixty-six older persons (≥ age 70) and their proxies were enrolled. Proxies rated patients' mobility using the MAT-sf as did the patients.

Results

The mean age of patients was 78.4 yr. (±6.2); 44% were female and 86% were white. Spouses made up 55% of the proxies, while 39% were children/in-laws. The correlation coefficient between patient and proxy MAT-sf scores was 0.81 (p < 0.01); a comparison of the slope of the regression line relating patient- and proxy-reported MAT-sf to a line of identity showed disagreement (p < 0.01), with proxy reports underreporting patient responses by 8.3% in lower mobility patients. The intra-class correlation characterizing agreement between repeated proxy reports 0.81.

Conclusion

Proxy reports of mobility in older patients have good reliability. However, in patients with poor mobility, the proxies tend to report a lower mobility than the patients.

Identifying older adults at risk of harm following elective surgery: a systematic review and meta-analysis

BACKGROUND

Elective surgeries can be associated with significant harm to older adults. The present study aimed to identify the prognostic factors associated with the development of postoperative complications among older adults undergoing elective surgery.

METHODS

Medline, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, and AgeLine were searched for articles published between inception and April 21, 2016. Prospective studies reporting prognostic factors associated with postoperative complications (composite outcome of medical and surgical complications), functional decline, mortality, post-hospitalization discharge destination, and prolonged hospitalization among older adults undergoing elective surgery were included. Study characteristics and prognostic factors associated with the outcomes of interest were extracted independently by two reviewers. Random effects meta-analysis models were used to derive pooled effect estimates for prognostic factors and incidences of adverse outcomes.

RESULTS

Of the 5692 titles and abstracts that were screened for inclusion, 44 studies (12,281 patients) reported on the following adverse postoperative outcomes: postoperative complications (n =28), postoperative mortality (n = 11), length of hospitalization (n = 21), functional decline (n = 6), and destination at discharge from hospital (n = 13). The pooled incidence of postoperative complications was 25.17% (95% confidence interval (CI) 18.03-33.98%, number needed to follow = 4). The geriatric syndromes of frailty (odds ratio (OR) 2.16, 95% CI 1.29-3.62) and cognitive impairment (OR 2.01, 95% CI 1.44-2.81) were associated with developing postoperative complications; however, there was no association with traditionally assessed prognostic factors such as age (OR 1.07, 95% CI 1.00-1.14) or American Society of Anesthesiologists status (OR 2.62, 95% CI 0.78-8.79). Besides frailty, other potentially modifiable prognostic factors, including depressive symptoms (OR 1.77, 95% CI 1.22-2.56) and smoking (OR 2.43, 95% CI 1.32-4.46), were also associated with developing postoperative complications.

CONCLUSION

Geriatric syndromes are important prognostic factors for postoperative complications. We identified potentially modifiable prognostic factors (e.g., frailty, depressive symptoms, and smoking) associated with developing postoperative complications that can be targeted preoperatively to optimize care.

Patient-Reported Outcome Measures (PROM) as A Preoperative Assessment Tool

AIM OF REVIEW

Patient-reported outcomes (PRO) on functional, social, and behavioral factors might be important preoperative predictors of postoperative outcomes. We conducted a literature review to explore associations of preoperative depression, socioeconomic status, social support, functional status/frailty, cognitive status, self-management skills, health literacy, and nutritional status with surgical outcomes.

METHODS

Two electronic data bases, including PubMed and Google Scholar, were searched linking either depression, socioeconomic status, social support, functional status/frailty, cognitive status, self-management skills, health literacy, or nutritional status with surgery, postoperative complications, or perioperative period within the past 2 decades.

RECENT FINDINGS

Preoperative depression has been linked to postoperative delirium, complications, persistent pain, longer lengths of stay, and mortality. Socioeconomic status associates with overall and cancer-free survival. Low socioeconomic status has also been connected to medication non- compliance. Social support can predict overall and cancer- free survival, as well as physical, social and emotional quality of life. Poor functional status and frailty have been related to postoperative complications, longer lengths of stay, post-discharge institutionalization, and higher costs. Preoperative cognitive impairment also associates with self-medication management errors, postoperative cognitive impairment, delirium, complications and mortality. In addition, a greater tendency for reduced adherence to preoperative medication instructions has been linked to health illiteracy. Preoperative malnutrition is prevalent and associates with postoperative morbidity.

CONCLUSION

Efficient and effective assessments of social and behavioral determinants of health, functional status, health literacy, patient's perception of health, and preferences for self-management may improve postoperative management and surgical outcomes, particularly among vulnerable patients undergoing elective surgery who might have subtle physical, social, or psychological deficits or challenges, otherwise missed upon routine evaluation. Patient Reported Outcome Measures (PROMs) can be used to effectively and efficiently collect these factors in the preoperative period, thereby identifying areas that can be intervened preemptively. (Partially Funded by the National Institute on Aging and the Wake Forest University Claude D. Pepper Older Americans Independence Center.).

Poor Performance on a Preoperative Cognitive Screening Test Predicts Postoperative Complications in Older Orthopedic Surgical Patients

BACKGROUND

The American College of Surgeons and the American Geriatrics Society have suggested that preoperative cognitive screening should be performed in older surgical patients. We hypothesized that unrecognized cognitive impairment in patients without a history of dementia is a risk factor for development of postoperative complications.

METHODS

We enrolled 211 patients 65 yr of age or older without a diagnosis of dementia who were scheduled for an elective hip or knee replacement. Patients were cognitively screened preoperatively using the Mini-Cog and demographic, medical, functional, and emotional/social data were gathered using standard instruments or review of the medical record. Outcomes included discharge to place other than home (primary outcome), delirium, in-hospital medical complications, hospital length-of-stay, 30-day emergency room visits, and mortality. Data were analyzed using univariate and multivariate analyses.

RESULTS

Fifty of 211 (24%) patients screened positive for probable cognitive impairment (Mini-Cog less than or equal to 2). On age-adjusted multivariate analysis, patients with a Mini-Cog score less than or equal to 2 were more likely to be discharged to a place other than home (67% vs. 34%; odds ratio = 3.88, 95% CI = 1.58 to 9.55), develop postoperative delirium (21% vs. 7%; odds ratio = 4.52, 95% CI = 1.30 to 15.68), and have a longer hospital length of stay (hazard ratio = 0.63, 95% CI = 0.42 to 0.95) compared to those with a Mini-Cog score greater than 2.

CONCLUSIONS

Many older elective orthopedic surgical patients have probable cognitive impairment preoperatively. Such impairment is associated with development of delirium postoperatively, a longer hospital stay, and lower likelihood of going home upon hospital discharge.

Self-Reported Function More Informative than Frailty Phenotype in Predicting Adverse Postoperative Course in Older Adults

BACKGROUND/OBJECTIVE

Current preoperative assessment tools such as the American College of Surgeons Surgical Risk Calculator (ACS Calculator) are suboptimal for evaluating older adults. The objective was to evaluate and compare the performance of the ACS Calculator for predicting risk of serious postoperative complications with the addition of self-reported physical function versus a frailty score.

DESIGN

Prospective cohort.

SETTING

Two tertiary care academic medical centers in Massachusetts.

PARTICIPANTS

Individuals aged 65 and older undergoing any surgery with a risk of serious complication of 5% or greater (N = 403).

MEASUREMENTS

We measured self-reported physical function using the Late-Life Function and Disability Instrument (LLFDI FUNCTION) and frailty phenotype (FP), which has a score ranging from 0 to 5 based on slow gait speed, weak handgrip, exhaustion, weight loss, or low activity. Using c-statistic and net classification improvement (NRI), we then analyzed capability of LLFDI-FUNCTION versus FP to improve the ACS Calculator for predicting an adverse postoperative course (serious complication, discharge to nursing home, readmission, death within 30 days of surgery). Increase in c-statistic and net reclassification improvement (NRI) for LLFDI-FUNCTION versus FP in addition to the ACS Calculator for predicting an adverse postoperative course (serious complication, discharge to nursing home, readmission, death within 30 days of surgery) RESULTS: Over 30 days, 26% of participants developed an adverse postoperative course. The increase in c-statistic for the ACS Calculator (baseline value 0.645) was slightly greater with LLFDI-FUNCTION (0.076) than with FP (0.058), with a bootstrapped difference in c-statistic of 0.005 (95% confidence interval = 0.002-0.007). NRI was also better with LLFDI-FUNCTION.

CONCLUSION

The LLFDI-FUNCTION predicted postoperative complications slightly better than the FP. Further studies are needed to confirm these findings and validate the use of the LLFDI-FUNCTION with the ACS Calculator for preoperative assessments of older adults.

Factors Associated with Patient-Initiated Telephone Calls After Spine Surgery

BACKGROUND

Telephone calls play a significant role in the follow-up care of postoperative patients. However, further data are needed to identify the determinants of patient-initiated telephone calls after surgery because these factors may also highlight potential areas of improvement in patient satisfaction and during the hospital discharge process. Therefore, the goal of this study is to determine the number of postoperative patient telephone calls within 14 days after surgery and establish the factors associated with patient-initiated calls and reasons for calling.

METHODS

A retrospective chart review of all spine surgeries performed at our institution from January 1, 2014, through January 2, 2015, was completed. Patient demographics, perioperative and operative variables, and telephone encounter data were collected. The primary outcome was a patient-initiated telephone call within 14 days after surgery. Secondary outcomes included reporting and analyzing the reasons for patient phone calls, analyzing which procedures were associated with the most telephone calls, and conducting a multivariate analysis to determine independent risk factors for patient calls.

RESULTS

Of the 488 patients who underwent surgical procedures, 222 patients (45.7%) made a telephone call within 14 days after surgery. There were 61 patients (27.48%) who called regarding pain control and 54 patients (23.87%) who called with bathing/dressing/wound questions. Other common categories include the following: other (21.17%), medication problems (15.77%), weight-bearing status/activity restrictions (5.14%), fever (3.15%), bowel management (1.35%), work notes (1.35%), and anticoagulation questions (0.45%). Factors associated with a telephone call within 14 days postoperatively included increased body mass index (P = 0.031), lower number of comorbidities (P = 0.043), telephone call within 2 weeks prior to surgery (P = 0.027), American Society of Anesthesiologists (ASA) score of 2 (P = 0.036), discharge disposition to home (P = 0.003), and elective procedure (P = 0.006). Multivariate analysis revealed that fusion procedures (odds ratio [OR], 2.16; 95% confidence interval [CI], 1.05-4.45; P = 0.037) and ASA score of 3-4 (OR, 0.55; 95% CI, 0.31-0.96, P = 0.036) were independently associated with increased and decreased propensity, respectively, toward making a phone call within 2 weeks.

CONCLUSIONS

Postoperative patient-initiated telephone calls within 14 days after spine surgery are very common, occurring after almost one half of all procedures. By evaluating such determinants, patient care can be improved by better addressing patient needs during and prior to discharge to prevent potential unnecessary postoperative calls and improve patient satisfaction.